Available models

A fast multimodal Qwen3.7 model with stronger vision, agent execution, and coding throughput than Qwen3.6 Flash. Built for low-latency multimodal understanding and agent workflows.

The Qwen3.7 flagship, optimized for coding, productivity, and agent-centric workloads. Its agent-oriented design emphasizes coding, office productivity, and complex multi-step work.

A cost-efficient multimodal Qwen model for general reasoning, vision, and production applications. It combines text and image understanding with a cost-conscious design for production-scale multimodal reasoning.

A 2.4T-parameter MoE flagship for coding, office productivity, vision, and long-horizon agents. Native multimodal understanding supports long documents and video, with strong end-to-end delivery on professional tasks.

An Anthropic model built for autonomous knowledge work, coding, and multimodal agents. It is positioned for autonomous knowledge work and coding with multimodal input, reasoning, and tool-oriented workflows.

A fast, efficient Claude model for latency-sensitive chat, coding, and agent tasks. It targets near-frontier intelligence at substantially lower latency and cost for high-volume interactive workloads.

A powerful Claude model for end-to-end coding and long-running professional workflows. It is optimized for agents that operate across complete software and professional workflows instead of isolated prompts.

An Opus model designed for long-running asynchronous agents and complex software workflows. The model is designed for asynchronous agents that sustain coding and professional work over extended runs.

A high-capability Opus model for long-context reasoning, coding, and multimodal analysis. It combines multimodal input, reasoning support, and a long context window for demanding general-purpose workflows.

Anthropic's flagship for demanding reasoning, coding, visual analysis, and long-running agents. It is especially capable at end-to-end software tasks, code review and bug finding, document and chart analysis, complex office deliverables, tool use, and coordinating parallel subagents.

A balanced frontier model for iterative development, agents, and professional knowledge work. Strengths include iterative development, complex codebase navigation, and end-to-end project execution with tools.

A frontier Sonnet model for coding, professional work, and adaptive agentic reasoning. Adaptive reasoning levels let applications balance frontier coding and agent performance against latency and token use.

The official DeepSeek V4 Flash model for fast long-context reasoning, coding, and agents. The 0731 post-training refresh keeps the mixture-of-experts architecture while strengthening agentic coding and tool use.

The official DeepSeek V4 Pro flagship for advanced reasoning, coding, and sustained agent workloads. The 0813 production checkpoint keeps 1M context and dual thinking modes under the same API name.

A fast Gemini thinking model for multi-turn chat, coding, and agent workflows. It offers near-Pro reasoning and tool use at Flash-class speed for multi-turn chat, coding, and agents.

A high-efficiency Gemini preview optimized for high-volume, latency-sensitive applications. It is tuned for high-volume workloads while approaching the quality of larger Flash models.

A frontier Gemini reasoning preview for software engineering and reliable agentic workflows. The preview improves software-engineering performance, agent reliability, and token efficiency across complex workflows.

An efficient multimodal Gemini model with strong coding, reasoning, and parallel-agent performance. It brings near-Pro coding and reasoning to a faster tier and is tuned for parallel agent execution.

A lightweight Gemini model for focused subagents and high-volume production tasks. The lightweight design is especially suited to focused subagents inside larger multi-agent systems.

A high-efficiency Gemini model for coding, agents, and web or application development. It focuses on polished coding and application outputs with fewer unnecessary edits across agentic workflows.

A high-efficiency Gemini workhorse for coding, agents, and knowledge work. It improves first-pass code accuracy, multi-step tool use, and production-ready application output over Gemini 3.6 Flash.

A native multimodal Kimi model for visual coding and coordinated agent workflows. It pairs native multimodal understanding with visual coding and a self-directed agent-swarm approach.

A multimodal Kimi model for long-horizon coding, UI generation, and agent orchestration. It targets long-horizon coding, code-driven UI generation, and coordinated multi-agent execution across complex projects.

A coding-focused Kimi model for reliable end-to-end programming across long contexts. The coding-focused design aims to complete end-to-end programming tasks reliably across long contexts.

An open-weight multimodal Kimi model for complex coding, reasoning, and agentic work. The open-weight multimodal reasoning model is positioned for complex coding, knowledge work, and long-running agents.

A flagship GPT model for advanced reasoning, coding, multimodal input, and professional workflows. It unifies general GPT and coding capabilities for large-context professional work and tool-driven execution.

A faster GPT-5.4 variant for high-throughput reasoning, coding, and multimodal applications. The smaller variant keeps strong reasoning and coding capabilities while improving speed and throughput.

A compact GPT model optimized for low-latency, high-volume, and cost-sensitive tasks. It is tuned for speed-critical classification, extraction, routing, and other high-volume lightweight tasks.

A frontier GPT model for complex professional work with stronger reasoning and reliability. It strengthens reliability and token efficiency on difficult professional tasks while retaining long-context support.

A fast, efficient GPT-5.6 model for chat, classification, and lightweight agents. The efficient tier targets high-volume chat, classification, and lightweight agent workflows with low latency.

The GPT-5.6 flagship for demanding reasoning, coding, and multi-step agent tasks. The flagship tier is particularly strong at command-line work and complex multi-step coding workflows.

A balanced GPT-5.6 model for everyday coding, reasoning, and agentic applications. The balanced tier sits between flagship quality and cost efficiency for everyday coding, reasoning, and agents.

A frontier Grok model for long-running agents, coding, and knowledge work. It focuses on multi-step agents, ambitious interactive and visual work, and sustained coding trajectories.

A long-context GLM reasoning model for project-level software engineering and agents. The large-scale reasoning model is intended for project-level software engineering and long-horizon agent workflows.

A flagship GLM model for long-horizon coding, agents, and security review. It keeps the GLM-5.2 base and raises coding and agent performance through post-training.

OpenAI's high-fidelity image generation and editing model for the dedicated Images API.